The Global System for Mobile communication (GSM) is currently the most popular standard for mobile telephones in the world and has been commercially deployed since the early 1990s. Although more recent standards for mobile communication in radio-based communication networks have been proposed, there is still an interest on the continued improvement of the GSM technology and its improvements, such as Enhanced Data rates for GSM Evolution (EDGE) also denoted Enhanced General Packet Radio Service (EGPRS) in the art. This means that improvements to the hardware and spectral efficiencies are still actively being sought.
With the advent of EGPRS phase 2 (EGPRS2) the GSM technology is reaching some of its limits in terms of complexity and performance. Firstly, the GSM physical layer uses single carrier modulation and highly time dispersive narrowband channels. Secondly, the need to increase the data rates and spectral efficiency has resulted in the introduction of higher order modulations. However, equalization of digitally modulated signals using these higher order modulations is a very demanding task for the receiver. The reason is that the computational complexity of the demodulator increases exponentially with the size of the symbol constellation of the modulation.
Given the time dispersion present in all GSM radio channels, the use of suboptimal receiver algorithms is unavoidable. Despite many simplifications these algorithms are still highly complex.
U.S. Patent Application No. 2008/0225985 discloses a technique for enhancing the capacity of a wireless communication channel by modulating data with a modulation scheme and transforming the modulated data from the frequency domain to the time domain. Bits are then encoded in a timeslot independence upon the time domain version of the modulated data. The document proposes using 40 pre-specified time domain values out of the 156 available in a burst, which requires 40 of the frequency domain symbols to be left as variables and cannot therefore carry any data. This process is, however, complicated and has high computational complexity.